Premium
Fast correlation registration method using singular value decomposition
Author(s) -
Zhang Mingchuan,
Yu KaiBor,
Haralick Robert M.
Publication year - 1986
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.4550010303
Subject(s) - singular value decomposition , computation , matching (statistics) , mathematics , correlation , pixel , image (mathematics) , algorithm , pattern recognition (psychology) , artificial intelligence , computer science , statistics , geometry
A new, fast template‐matching method using the Singular Value Decomposition (SVD) is presented. This approach involves a two‐stage algorithm, which can be used to increase the speed of the matching process. In the first stage, the reference image is orthogonally separated by the SVD and then low‐cost pseudo‐correlation values are calculated. This reduces the number of computations to 2* N * L instead of N 2 L 2 , where L × L is the size of the reference image and N × N is the original image size. At the second stage, a small group of values near the maximum pseudo‐correlation is selected. the true correlation for the small number of pixels in this group is them computed precisely in the second stage. Experimental and analytic results are presented to show how the computation complexity is greatly improved.